Guanglin Zhang

Capacity of Hybrid Wireless Networks with Directional Antenna and Delay Constraint

We study the throughput capacity of hybrid wireless networks with a directional antenna. The hybrid wireless network consists of n randomly distributed nodes equipped with a directional antenna, and m regularly placed base stations connected by optical links. We investigate the ad hoc mode throughput capacity when each node is equipped with a directional antenna under an L-maximum-hop resource allocation. That is, a source node transmits to its destination only with the help of normal nodes within L hops. Otherwise, the transmission will be carried out in the infrastructure mode, i.e., with the help of base stations. We find that the throughput capacity of a hybrid wireless network greatly depends on the maximum hop L, the number of base stations m, and the beamwidth of directional antenna θ. Assuming the total bandwidth W bits/sec of the network is split into three parts, i.e., W₁ for ad hoc mode, W₂ for uplink in the infrastructure mode, and W₃ for downlink in the infrastructure mode. We show that the throughput capacity of the hybrid directional wireless network is Θ(nW₁/θ² L log n) + Θ(mW₂), if L = Ω(n^1/3/θ^4/3 log^2/3 n); and Θ((θ²L² log^2/3 n); and + Θ(mW₂), if L = o(n^1/3/θ^4/3 log^2/3 n), respectively. Finally, we analyze the impact of L, m and θ on the throughput capacity of the hybrid networks.

Multicast Capacity for VANETs with Directional Antenna and Delay Constraint

Vehicular Ad Hoc Networks (VANETs) with base stations are called hybrid VANET, where base stations are deployed to improve the throughput capacity. In this paper, we study the multicast throughput capacity for hybrid wireless VANET with a directional antenna on each vehicle and the end-to-end delay is constrained. In the hybrid VANET, there are n mobile vehicles (or nodes) distributed in a unit area with m strategically deployed base stations connected using high-bandwidth wire links. There are n_s multicast sessions and each multicast session has one source which transmits identical data to its associated p destinations. We investigate the multicast throughput capacity for two mobility models with two mobility scales, respectively, while each vehicular node is equipped with a directional antenna and with a tolerant delay D. That is, a source node transmits to its p destinations only with the help of normal nodes within D consecutive time slots. Otherwise, the transmission will be performed with in the infrastructure mode, i.e., with the help of base stations. We demonstrate that the one dimensional i.i.d. slow mobility pattern catch the main feature of VANETs. And we find that the multicast throughput capacity of the hybrid wireless VANET greatly depends on the delay constraint D, the number of base stations m, and the beamwidth of directional antenna θ. In the order of magnitude, we obtain the closed form of the multicast throughput capacity of the hybrid directional VANET, where the impact of D, m and θ on the multicast throughput capacity is analyzed. Moreover, we derive the lower bound of the muticast throughput using a similar raptor coding approach.

Percolation Degree of Secondary Users in Cognitive Networks

A cognitive network refers to the one where two overlaid structures, called primary and secondary networks coexist. The primary network consists of primary nodes who are licensed spectrum users while the secondary network comprises unauthorized users that have to access the licensed spectrum opportunistically. In this paper, we study the percolation degree of the secondary network to achieve k-percolation in large scale cognitive radio networks. The percolation degree is defined as the number of nearest neighbors for each secondary user when there are at least k vertex-disjoint paths existing between any two secondary relays in the percolated cluster. The percolated cluster is formed when there are an infinite number of mutually connected secondary users spanning the whole network. Each user in the cluster is possibly connected to several neighbors, inducing more communication links between any two of them. Since nodes located near the boundary have fewer neighbors, the boundary effect becomes a bottleneck in determining the percolation degree. For cognitive networks, when the primary node density becomes considerably large, the boundary effect spreads inside the network. The transmission area of most secondary users who are located near the primary nodes decreases due to the restriction of the primary network. Therefore, to ensure k-connectivity in the percolated cluster, each secondary user must be connected to more neighbors, and the percolation degree of the secondary network yields a function of the primary node density. We specify the relationship into three regimes regarding the topology variation of the cognitive network. A closed-form expression of the percolation degree under different primary node densities is presented. The expression characterizes the connectivity strength in the secondary percolated cluster, therefore providing analytical insight on fault tolerance improvement in cognitive networks.

Cost Minimizing Online Algorithms for Energy Storage Management With Worst-Case Guarantee

The fluctuations of electricity prices in demand response schemes and intermittency of renewable energy supplies necessitate the adoption of energy storage in microgrids. However, it is challenging to design effective real-time energy storage management strategies that can deliver assured optimality, without being hampered by the uncertainty of volatile electricity prices and renewable energy supplies. This paper presents a simple effective online algorithm for the charging and discharging decisions of energy storage that minimizes the electricity cost in the presence of electricity price fluctuations and renewable energy supplies, without relying on the future information of prices, demands, or renewable energy supplies. The proposed algorithm is supported by a near-best worst-case guarantee (i.e., competitive ratio), as compared with the offline optimal decisions based on full future information. Furthermore, the algorithm can be adapted to take advantage of limited future information, if available. By simulations on real-world data, it is observed that the proposed algorithms can achieve satisfactory outcomes in practice.

Cost Minimization Online Energy Management for Microgrids with Power and Thermal Storages

In this paper, we consider a typical microgrid scenario that consists of centralized power grid, renewable energy generation, and combined heat and power (CHP) local (co-)generation, as well as power and heat energy storage devices. We aim to minimize the microgrids operating cost by formulating it as a stochastic non-convex optimization programming, which is challenging to solve optimally. We design an online algorithm by developing a modified Lyapunov optimization approach based on the random system inputs (e.g., the acquired electricity from power grid, the charging/discharging of the energy storage devices, obtained power from the local generator, and the renewable energy generation etc.), which does not require any statistic information of the system. Considering that the nonconvexity of the problem is caused by the dependence of power in battery pack and heat energy in thermal tank, we further explore the relation between them and convert the problem into a convex stochastic optimization programming. We show that the proposed algorithm is efficient with very low computational complexity and is proved to achieve near optimal performance. Moreover, extensive empirical evaluations using real-world traces are provided to study the effectiveness of the proposed algorithm.

Multicast Capacity for Hybrid MANETs with Direction Antenna and Delay Constraint

We study the multicast throughput capacity for hybrid wireless mobile ad hoc networks (MANETs) with a directional antenna and delay constraint. The hybrid wireless network consists of a mobile ad hoc network with

Multicast capacity of cache enabled content-centric wireless Ad Hoc networks

n

Capacity of Content-Centric Hybrid Wireless Networks

nodes and

Multipath network coding and multicasting for content sharing in wireless P2P networks: A potential game approach

m

Dynamics of multipath network coding and multicasting in wireless P2P networks

regularly placed base stations connected by high-bandwidth wired links. For the MANET, there are